I’m trying to code using package “rstan” in R my own joint likelihood function for the MCMC sampling to run on. Currently I have:

M<-'

functions{

real newexp_lpdf(vector x, real r, real mu){

vector[num_elements(x)] prob;

real lprob;

for (i in 1:num_elements(x)){

prob[i] = -r/mu*(gamma_p(r+1,(x[i]+1)*mu) ;

}

}

lprob = sum(log(prob));

return lprob;

}

}

data {

int N;

vector[N] Y;

}

parameters {

real <lower=0> mu;

real <lower=0> r;

}

model {

real alpha;

real beta;

alpha = 1.0;

beta = 1.0;

mu ~ gamma(alpha, beta);

r ~ gamma(alpha, beta);

Y ~ newexp(r,mu);

}

’

My question is, if my observed data Y contains multiple data points per observation. That is, instead of observing (Y1, Y2,…Yn), observe (A1, B1, C1, D1), (A2, B2, C2, D2), …(An, Bn, Cn, Dn). Is there a way I can code the observed “vectors” as:

vector~ newexp(r, mu)

Instead of Y~ newexp(r,mu)?

Thanks for your help.